Organization
14 Interestana reports mention Google Research, newest first. Each is summarised from the original reporting and links back to its publisher.
Google Research has released a tutorial detailing Regularized Recursive Self-Improvement (RRSI), a novel method designed to empower Large Language Model (LLM) agents to autonomously rewrite and enhance their own underlying architecture.
A prevailing paradox of public sentiment towards artificial intelligence is currently being observed, characterized by widespread skepticism and apprehension coexisting with rapidly increasing AI adoption. This dichotomy suggests a complex relationship where individuals express negative views on AI's societal impact…
Google Research has introduced an AI video co-director designed to generate coherent, minutes-long videos by addressing two primary failures in current multi-shot AI video pipelines: identity drift and cascading errors.
Google Research has introduced Retrieve-for-Train (R4T), a new framework designed to address the challenge of returning diverse sets of results for search and recommendation queries, rather than just a single best match.
Google DeepMind and Google Research have released WeatherNext 3, an advanced AI weather model designed to overcome limitations in resolution and initialization time inherent in traditional physics-based forecasting. This new model addresses the issue of coarse resolution, which previously hindered…
Google Research has announced the release of TimesFM-3, a significant advancement in time series forecasting. This new foundation model boasts 330 million parameters and is specifically engineered for zero-shot multivariate forecasting, meaning it can predict multiple related time series simultaneously…
Google Research and UNSW Sydney have introduced GlucoFM, a novel self-supervised foundation model designed for continuous glucose monitoring (CGM). This model distinguishes itself by employing a dual-stream architecture, a departure from prior CGM models such as CGMformer, GluFormer, and CGM-JEPA…
Google Research, in collaboration with the University of Southern California (USC), has introduced Mobility-Embedded POIs (ME-POIs), a novel framework designed to enhance text-based place embeddings by incorporating aggregate human movement data.
Google Research introduced SensorFM, a foundation model for wearable health, pre-trained on more than 1 trillion minutes of sensor data collected from 5 million individuals. This model is designed to address the limitations of building individual models for each health…
Google Research introduced TabFM, a novel foundation model designed specifically for tabular data, on an unspecified recent date. This model is capable of performing both classification and regression tasks without requiring dataset-specific training, a significant departure from traditional machine learning…
Google researchers have developed a method to detect AI-generated spam by analyzing the network infrastructure used to distribute it, rather than solely focusing on the content itself. This approach, detailed in a Google Research blog post, aims to identify patterns…